Does the Effect of Pollution on Infant Mortality Differ Between Developing and Developed Countries? Evidence from Mexico City

Motivation

Overview

• Context: Mexico 1997 – 2006
  • Rapidly industrializing during this time period
  • Also implemented policies aimed at improving air quality
• Methods: fixed effects and IV using thermal inversions
• Findings:
  • Evidence that pollution increases infant mortality
  • Compared to the US, larger marginal effects for CO and similar marginal effects for PM₁₀
• Concern: other factors may be correlated with health
  • Weather, socio-economic status and changes in economic conditions

Empirical Strategy

Fixed Effects

Objective: estimate \beta_1 the relationship between pollution (P_{mw}) in a municipality (m) in a given week (w) and mortality per 100,000 live births (Y_{mw}) Y_{mw} = \beta_0 + \beta_1 P_{mw} + \alpha_m + \sigma_{mj} + \epsilon_{mw}

• \alpha_m is a set of municipality fixed effects that control for permanent differences across municipalities
• \sigma_{mj} is a set of bimonthly x municipality fixed effects, which control for common factors in a given two month block that could affect both pollution levels and infant mortality within a municipality

Empirical Strategy

Fixed Effects

Y_{mw} = \beta_0 + \beta_1 P_{mw} + \alpha_m + \sigma_{mj} + \epsilon_{mw}

Concerns:

• Unobserved, time-varying differences across municipalities will bias \beta_1
• Classical measurement error in the pollution variable will bias \beta_1 downwards

Empirical Strategy

Instrumental Variables

Objective: test whether inversions increase the concentrations of different types of pollutants \rightarrow use the number of thermal inversions in a given week (TI_w) to instrument for pollution

\begin{align*} P_{mw} &= \pi_0 + \pi_1 TI_w + \sum \pi_{2m} w + h(W_{mw}) + \alpha_m + \sigma_{mj} + \mu_{mw} \\ Y_{mw} &= \beta_0 + \beta_1 P_{mw} + \sum \beta_{2m} w + h(W_{mw}) + \alpha_m + \sigma_{mj} + \epsilon_{mw} \end{align*}

• TI_w varies at the week level so week by year fixed effects are not identified
  • control for municipality-specific week by year trends (w)
• municipality fixed effects (\alpha_m) control for time-invariant characteristics across municipalities
• bimonthly x municipality fixed effects (\sigma_{mj}) control for seasonal effects within each municipality
• h(W_{mw}) is a set of controls for temperature and weather conditions

Empirical Strategy

Instrumental Variables

\begin{align*} P_{mw} &= \pi_0 + \pi_1 TI_w + \sum \pi_{2m} w + h(W_{mw}) + \alpha_m + \sigma_{mj} + \mu_{mw} \\ Y_{mw} &= \beta_0 + \beta_1 P_{mw} + \sum \beta_{2m} w + h(W_{mw}) + \alpha_m + \sigma_{mj} + \epsilon_{mw} \end{align*}

Concerns:

• Residual seasonal variation
• Short time frame (such as week) may overstate the effect
• Exclusion restriction may be violated
• Single instrument for all pollutants

Results

IV First Stage

Results

IV

Results

IV, Cause of Death

Results

IV, Multiple Pollutants

Results

Comparison with US

Summary

• Statistically significant effects of pollution on infant mortality
• Compared to US:
  • Larger effects for CO
  • Comparable estimates for PM₁₀, despite much higher levels
• Policy decisions need to consider the different effects in developing countries
  • May understate the benefits from environmental regulation